Racial Disparities in Mental HealthDetroit Area Study, 1995: Social Influence on Health: Stress, Racism, and
Health Protective Resources03272SociologyRaceHealthLinear regressionExploratoryInter-university Consortium for Political and Social Research. Racial Disparities in
Mental Health: A Data-Driven Learning Guide. Ann Arbor, MI: Inter-university Consortium for
Political and Social Research [distributor], 2009-04-16.
Doi:10.3886/racementalhealthGoal & Concept

Goal

This exercise will investigate racial disparities in mental illness, particularly
differences in reports of depression between African American and White adults.
Crosstabulation and linear regression will be used.

Concept

Race is a social category of people labeled and treated as similar because of some common
traits, such as skin color, texture of hair, and shape of eyes. Racial categories are
not natural, biological categories. Different societies identify different
characteristics that distinguish one race from another. Racial categories are often
reflected social rankings and access to resources.

Numerous disciplines study mental health and illness. The sociological approach to mental
health focuses on the social conditions that influence psychological functioning as well
as the processes linking social conditions and psychological well-being. Researchers
might use measures such as self-reported mental health, medical diagnoses, scales
representing symptoms of mental disorders, or number of work days missed due to mental
illness.

Evidence shows that mental health disorders are not randomly distributed throughout
society but tend to be higher among minority racial groups. Race can be an important
predictor of exposure to stress, coping strategies, and social support and, in turn,
mental health status. For example, experiences of discrimination are stressful events
that place minorities at risk for depression and anxiety.

Examples of possible research questions about race and mental health:

How is race related to self-rated mental health?

How is race related to seeking medical treatment for mental health disorders?

Are racial differences in treatment of mental health disorders related to
differences in insurance coverage?

To what extent can differences in mental health by race be explained by differences
in income, education, and marital status?

To what extent can racial differences in mental health be explained by differences
in experiences of discrimination?

Dataset

Data for this exercise come from the Detroit Area Study, 1995: Social Influence on Health. Researchers at the
University of Michigan conducted the survey of adults aged 18 and older residing in
households located in the Michigan counties of Oakland, Macomb, and Wayne.

The Detroit Area Study was conducted nearly every year from 1951 through 2005. The 1995
survey explored the ways in which social influences such as stress and racism affected
respondents' health and outlook on life. Respondents were asked about their physical and
mental health status and the effects these had on daily activities. Respondents were
also asked about their experiences with employment, crime, discrimination, alcohol and
drug use, fears and phobias, and medical treatment. A final set of questions gathered
demographic information such as highest level of education completed and total family
income in 1994.

This exercise will use the following variables:

Frequency of feeling sad (V226)

Self-reported race (V118)

Highest grade of school completed (V1001)

Marital status (V107)

Ever treated unfairly because of race or ethnicity (V125)

Application

This exercise explores the relationship between race and reported levels of depression
using crosstabulation and linear regression.

Crosstabulation

Depression was measured with the question, "how often do you feel so sad that nothing
could cheer you up?" (V226) The response options were "very often," "fairly often," "not
too often," "hardly ever," and "never." Fewer than 10 percent of respondents said "very
often" or "fairly often," so we created a new variable (called V226NEW) that combined
these two categories and reversed the coding so that higher numbers meant higher
frequency of depression.

Begin by examining the distribution of
responses to V226NEW. This will show you how many people chose each
answer category. What percent of people said that they hardly ever felt
sadand how many people was that?

In this survey, respondents were asked to identify the race that best describes them.
Look at the distribution of
responses to this variable (V118). As you can see, very few selected
Asian, American Indian, Hispanic, or other. For this exercise we dropped these
respondents in order to compare only Black and White respondents. V118NEW is the recoded
where Black is coded as "1" and White is coded as "0".

To see whether Blacks and Whites report feeling sad with similar frequencies, look at a
crosstab of V226new with V118new. What do you find? What percent of
Whites report feeling sad very or fairly often? What percent of Blacks do? What about
never feeling sad?

Multiple Regression

One concern when studying race and mental health is that the relationship between race
and depression may be caused by a third factor. Next we will use multiple regression to
control for potential confounding factors and isolate the relationship between race and
reports of depression. In addition to race and depression, we will include the following
measures (the links take you to frequency distributions of each):

Education level (V1001new) will be included in a measure of
socioeconomic status. Previous studies have shown that depression rates may be
higher among people with lower socioeconomic standing.

Marital status (V107new) will be included because research has shown
that rates of depression tend to be higher among single people than married
people.

Discrimination (V125new)

Note, we recoded education (V1001) into V1001new which collapses the answers from
specific years of schooling completed to categories that represent less than high
school, high school degree, and so on. We recoded V107 so that respondents were
considered either married or not married rather than retaining all categories of "not
married" (divorced, single, etc.). Lastly, we removed the two people who answered "Don't
know" to the question about discrimination, creating V125new.

Can you think of other factors that might confound the relationship between race and
feelings of depression?

First, we start by including only race and
frequency of feeling sad in the regression. How would you interpret the
outcome? How would you compare the regression results to the results of the
crosstabulation you conducted? (Hint: to understand regression results, look at the B
value and the Probability. The B value tells the strength and direction of the
relationship and the probability tells you if the relationship is significant. If you
need more help with the interpretation, see the Interpretation Guide on the next
tab.

Next the control variables are added to the regression.

What do you find? How would you interpret the coefficient on race? How has the
coefficient changed compared to the previous model without control variables? How would
you interpret the coefficients on the other variables in the model? What can you say
about the relationship between race and depression overall based on these models?

Interpretation & Summary

Think about your answers to the application questions before you click through to the
interpretation guide for help in answering them.

What percent of people said that they hardly ever felt sad and how
many people was that?

Did there appear to be a relationship between race and depression based on the
crosstabulation? What percent of Whites report feeling sad very or fairly often?
What percent of Blacks do? What about never feeling sad?

Can you think of other factors that might confound the relationship between race and
feelings of depression?

How would you interpret the outcome regression with race as an independent variable
and depression as the dependent? How would you compare the regression results to the
results of the crosstabulation you conducted?

What about the results for the regression with controls? How would you interpret the
coefficient on race? How has the coefficient changed compared to the previous model
without control variables? How would you interpret the coefficients on the other
variables in the model? What can you say about the relationship between race and
depression overall based on these models?

Interpretation

Things to think about when interpreting the results:

It is important to look at the amount of missing data in each relationship
and think about the ways in which that might affect the generalizability of
the results. Most of these analyses have very small amounts of missing data
so that would not be as much of a concern here. Because the survey was done
with a probability sample and sample weights were included on the analyses,
the results are likely to be fairly representative of people living in
greater Detroit.

Reading the results: the numbers in each cell of the
crosstabulation tables show the percent of the people who fall into the
overlapping categories, followed by the actual number of people that
represents in this sample. The coloring in the tables demonstrates how the
observed numbers in each cell compares to the expected number if there were
no association between the two variables. The accompanying bar charts
display the patterns visually as well.

Regression is a statistical technique that tests for the effects of one
variable on another. A bivariate regression includes the dependent variable
and a single independent variable while a multiple regression includes the
dependent variable and two or more independent or control variables. To
quickly interpret regression results, look at the B value and the
probability. The B value tells the amount and direction of change in the
dependent variable caused by one unit increase in the value of the
independent variable. The "p-value" or probability tells whether this change
is likely due to change -- generally a probability of .05 or less is
considered not due to chance.

Main Findings:

Rates of depression in the study were low. The majority of the respondents
say they feel so sad that nothing could cheer them up hardly ever or never
(71%), and less than 10% of respondents said they feel that sad very often
or fairly often.

The crosstab indicates Black respondents report feeling sad more frequently
than White respondents. Among the Black respondents, about 10% reported
feeling sad very often or fairly often, compared to about 9% of Whites. At
the other extreme, 44% of Black respondents said that they never feel that
sad as compared to about 48% of the white respondents.

The bivariate regression shows a very slight relationship between race and
depression. A positive coefficient of race means that, on average, Black
respondents reported feeling sad more frequently than Whites (Because Blacks
are coded the higher number [1] on the race variable and 4 represents
feeling sad very often or fairly often). The coefficient of race was
positive, but it was not statistically significant so we would say there is
no significant relationship between race and depression.

The multivariate regression analysis added variables that might be related
to both race and reports of depression (education, marital status, and
experience of discrimination). In this model, the coefficient of race has
changed direction (negative means Blacks reported feeling sad less than
whites when education, marital status, and discrimination are taken into
account), but still is not statistically significant.

The relationship between education level and feelings of depression is
significant in the model. The negative coefficient of education tells us
that as the level of education increases, the frequency of feeling sad
decreases. However, we can not conclude that level of
education causes fewer feelings of depression. It could also
be the case that feelings of depression limit the amount of education
individuals receive.

Experiences with discrimination are associated with significant differences
in reports of feeling sad. On average, people who have experienced
discrimination report feeling sad more often than people who have not
experienced discrimination.

Taken together, these findings suggest that experiences of discrimination
and lower education might account for the pattern of Blacks reporting
feeling sad more often. (Further analyses indicate that Blacks have, on average, lower
levels of education than Whites and are also far more likely to report
experiencing discrimination (68% of Blacks compared to 16% of Whites).

Summary

The goal of this exercise was to examine the relationship between race and mental
health as measured by feelings of sadness or depression. Taken together, the results
show that, contrary to the pattern suggested in the initial crosstabulation table,
there are no significant differences in reports of depression by race. However,
having a lower level of education and experiences with discrimination are related to
higher frequencies of feeling sad. The use of multivariate regression emphasizes
about importance of confounding factors which could help explain an apparent
relationship between race and depression.